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Add MP tag
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‎authors/glebbelov/miscellaneous/nqueens.ipynb‎

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"\n",
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"Description: How can N queens be placed on an NxN chessboard so that no two of them attack each other?\n",
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"\n",
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"Tags: amplpy, constraint-programming, highlights\n",
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"Tags: amplpy, MP, constraint-programming, highlights\n",
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"\n",
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"Notebook author: Gleb Belov <<gleb@ampl.com>>"
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]
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"provenance": []
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},
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"kernelspec": {
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"display_name": "Python 3.9.13 ('venv': venv)",
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.13 (main, May 24 2022, 21:28:31) \n[Clang 13.1.6 (clang-1316.0.21.2)]"
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"version": "3.13.0"
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},
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"vscode": {
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"interpreter": {
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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"nbformat_minor": 4
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‎authors/glebbelov/miscellaneous/sched_numberof.ipynb‎

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"\n",
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"Description: Scheduling model with the Constraint Programming *numberof* operator, solved with a MIP solver. New MIP solver drivers based on the [MP library](https://amplmp.readthedocs.io/) enable CP-style modeling.\n",
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"\n",
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"Tags: ampl-only, constraint-programming\n",
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"Tags: ampl-only, MP, constraint-programming\n",
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"\n",
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"Notebook author: Gleb Belov <<gleb@ampl.com>>\n",
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"\n",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.6"
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"version": "3.13.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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"nbformat_minor": 4
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}

‎authors/glebbelov/miscellaneous/sol-check.ipynb‎

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"\n",
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"Description: Pathological examples to illustrate MP solution checker and settings\n",
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"\n",
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"Tags: MP library, solution check, non-continuous objective, strict comparison\n",
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"Tags: MP, solution check, non-continuous objective, strict comparison\n",
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"\n",
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"Notebook author: Gleb Belov <<gleb@ampl.com>>"
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]
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.6"
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"version": "3.13.0"
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},
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"vscode": {
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"interpreter": {
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

‎authors/glebbelov/portfolio/portfolio_factor_model.ipynb‎

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"\n",
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"Description: Mean-Variance Portfolio Optimization model where the risk estimator is not given explicitly but is instead represented by a factor model, as is common in US equity models [1]. The original notebook is [3].\n",
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"\n",
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"Tags: finance, portfolio optimization, mean variance, factor model, AMPL conditonal instantiation, cardinality constraint\n",
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"Tags: finance, portfolio optimization, mean variance, factor model, AMPL conditonal instantiation, MP, cardinality constraint\n",
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"\n",
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"Notebook author: Gleb Belov <<gleb@ampl.com>>\n",
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"\n",

‎authors/glebbelov/scheduling/color_change/color_change_scheduling.ipynb‎

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"\n",
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"Description: A scheduling problem demonstrating high-level modeling and automatic solver tuning in FICO Xpress\n",
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"\n",
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"Tags: amplpy, scheduling, color change scheduling, tuning, xpress\n",
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"Tags: AMPLPY, MP, scheduling, color change scheduling, tuning, xpress\n",
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"\n",
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"Notebook author: Gleb Belov <<gleb@ampl.com>>\n",
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"\n",

‎docs/source/authors/gleb_at_ampl.com.rst‎

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| `Notebooks <../notebooks/index.html>`_ > `CP-style scheduling model with the *numberof* operator, solved by a MIP solver <../notebooks/cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver.html>`_
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| |github-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |colab-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |deepnote-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |kaggle-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |gradient-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |sagemaker-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver|
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| Description: Scheduling model with the Constraint Programming *numberof* operator, solved with a MIP solver. New MIP solver drivers based on the [MP library](https://amplmp.readthedocs.io/) enable CP-style modeling.
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| Tags: :ref:`tag-ampl-only`, :ref:`tag-constraint-programming`
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| Tags: :ref:`tag-ampl-only`, :ref:`tag-mp`, :ref:`tag-constraint-programming`
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| Author: :ref:`email-gleb_at_ampl.com` <gleb@ampl.com>
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.. |github-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| image:: https://img.shields.io/badge/github-%23121011.svg?logo=github
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| `Notebooks <../notebooks/index.html>`_ > `N-Queens <../notebooks/n-queens.html>`_
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| |github-n-queens| |colab-n-queens| |deepnote-n-queens| |kaggle-n-queens| |gradient-n-queens| |sagemaker-n-queens|
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| Description: How can N queens be placed on an NxN chessboard so that no two of them attack each other?
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| Tags: :ref:`tag-amplpy`, :ref:`tag-constraint-programming`, :ref:`tag-highlights`
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| Tags: :ref:`tag-amplpy`, :ref:`tag-mp`, :ref:`tag-constraint-programming`, :ref:`tag-highlights`
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| Author: :ref:`email-gleb_at_ampl.com` <gleb@ampl.com>
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.. |github-n-queens| image:: https://img.shields.io/badge/github-%23121011.svg?logo=github
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| `Notebooks <../notebooks/index.html>`_ > `Paintshop Color Change Scheduling with FICO Xpress <../notebooks/paintshop-color-change-scheduling-with-fico-xpress.html>`_
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| |github-paintshop-color-change-scheduling-with-fico-xpress| |colab-paintshop-color-change-scheduling-with-fico-xpress| |deepnote-paintshop-color-change-scheduling-with-fico-xpress| |kaggle-paintshop-color-change-scheduling-with-fico-xpress| |gradient-paintshop-color-change-scheduling-with-fico-xpress| |sagemaker-paintshop-color-change-scheduling-with-fico-xpress|
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| Description: A scheduling problem demonstrating high-level modeling and automatic solver tuning in FICO Xpress
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| Tags: :ref:`tag-amplpy`, :ref:`tag-scheduling`, :ref:`tag-color-change-scheduling`, :ref:`tag-tuning`, :ref:`tag-xpress`
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| Tags: :ref:`tag-amplpy`, :ref:`tag-mp`, :ref:`tag-scheduling`, :ref:`tag-color-change-scheduling`, :ref:`tag-tuning`, :ref:`tag-xpress`
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| Author: :ref:`email-gleb_at_ampl.com` <gleb@ampl.com>
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.. |github-paintshop-color-change-scheduling-with-fico-xpress| image:: https://img.shields.io/badge/github-%23121011.svg?logo=github
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| `Notebooks <../notebooks/index.html>`_ > `Portfolio Optimization: Factor Model <../notebooks/portfolio-optimization-factor-model.html>`_
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| |github-portfolio-optimization-factor-model| |colab-portfolio-optimization-factor-model| |deepnote-portfolio-optimization-factor-model| |kaggle-portfolio-optimization-factor-model| |gradient-portfolio-optimization-factor-model| |sagemaker-portfolio-optimization-factor-model|
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| Description: Mean-Variance Portfolio Optimization model where the risk estimator is not given explicitly but is instead represented by a factor model, as is common in US equity models [1]. The original notebook is [3].
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| Tags: :ref:`tag-finance`, :ref:`tag-portfolio-optimization`, :ref:`tag-mean-variance`, :ref:`tag-factor-model`, :ref:`tag-ampl-conditonal-instantiation`, :ref:`tag-cardinality-constraint`
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| Tags: :ref:`tag-finance`, :ref:`tag-portfolio-optimization`, :ref:`tag-mean-variance`, :ref:`tag-factor-model`, :ref:`tag-ampl-conditonal-instantiation`, :ref:`tag-mp`, :ref:`tag-cardinality-constraint`
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| Author: :ref:`email-gleb_at_ampl.com` <gleb@ampl.com>
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.. |github-portfolio-optimization-factor-model| image:: https://img.shields.io/badge/github-%23121011.svg?logo=github
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| `Notebooks <../notebooks/index.html>`_ > `Solution check: discontinuous objective function <../notebooks/solution-check-discontinuous-objective-function.html>`_
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| |github-solution-check-discontinuous-objective-function| |colab-solution-check-discontinuous-objective-function| |deepnote-solution-check-discontinuous-objective-function| |kaggle-solution-check-discontinuous-objective-function| |gradient-solution-check-discontinuous-objective-function| |sagemaker-solution-check-discontinuous-objective-function|
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| Description: Pathological examples to illustrate MP solution checker and settings
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| Tags: :ref:`tag-mp-library`, :ref:`tag-solution-check`, :ref:`tag-non-continuous-objective`, :ref:`tag-strict-comparison`
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| Tags: :ref:`tag-mp`, :ref:`tag-solution-check`, :ref:`tag-non-continuous-objective`, :ref:`tag-strict-comparison`
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| Author: :ref:`email-gleb_at_ampl.com` <gleb@ampl.com>
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.. |github-solution-check-discontinuous-objective-function| image:: https://img.shields.io/badge/github-%23121011.svg?logo=github

‎docs/source/index.rst‎

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| `Notebooks <notebooks/index.html>`_ > `CP-style scheduling model with the *numberof* operator, solved by a MIP solver <notebooks/cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver.html>`_
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| |github-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |colab-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |deepnote-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |kaggle-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |gradient-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |sagemaker-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver|
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| Description: Scheduling model with the Constraint Programming *numberof* operator, solved with a MIP solver. New MIP solver drivers based on the [MP library](https://amplmp.readthedocs.io/) enable CP-style modeling.
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| Tags: :ref:`tag-ampl-only`, :ref:`tag-constraint-programming`
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| Tags: :ref:`tag-ampl-only`, :ref:`tag-mp`, :ref:`tag-constraint-programming`
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| Author: :ref:`email-gleb_at_ampl.com` <gleb@ampl.com>
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.. |github-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| image:: https://img.shields.io/badge/github-%23121011.svg?logo=github
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| `Notebooks <notebooks/index.html>`_ > `N-Queens <notebooks/n-queens.html>`_
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| |github-n-queens| |colab-n-queens| |deepnote-n-queens| |kaggle-n-queens| |gradient-n-queens| |sagemaker-n-queens|
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| Description: How can N queens be placed on an NxN chessboard so that no two of them attack each other?
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| Tags: :ref:`tag-amplpy`, :ref:`tag-constraint-programming`, :ref:`tag-highlights`
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| Tags: :ref:`tag-amplpy`, :ref:`tag-mp`, :ref:`tag-constraint-programming`, :ref:`tag-highlights`
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| Author: :ref:`email-gleb_at_ampl.com` <gleb@ampl.com>
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.. |github-n-queens| image:: https://img.shields.io/badge/github-%23121011.svg?logo=github
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| `Notebooks <notebooks/index.html>`_ > `Paintshop Color Change Scheduling with FICO Xpress <notebooks/paintshop-color-change-scheduling-with-fico-xpress.html>`_
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| |github-paintshop-color-change-scheduling-with-fico-xpress| |colab-paintshop-color-change-scheduling-with-fico-xpress| |deepnote-paintshop-color-change-scheduling-with-fico-xpress| |kaggle-paintshop-color-change-scheduling-with-fico-xpress| |gradient-paintshop-color-change-scheduling-with-fico-xpress| |sagemaker-paintshop-color-change-scheduling-with-fico-xpress|
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| Description: A scheduling problem demonstrating high-level modeling and automatic solver tuning in FICO Xpress
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| Tags: :ref:`tag-amplpy`, :ref:`tag-scheduling`, :ref:`tag-color-change-scheduling`, :ref:`tag-tuning`, :ref:`tag-xpress`
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| Tags: :ref:`tag-amplpy`, :ref:`tag-mp`, :ref:`tag-scheduling`, :ref:`tag-color-change-scheduling`, :ref:`tag-tuning`, :ref:`tag-xpress`
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| Author: :ref:`email-gleb_at_ampl.com` <gleb@ampl.com>
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.. |github-paintshop-color-change-scheduling-with-fico-xpress| image:: https://img.shields.io/badge/github-%23121011.svg?logo=github
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| `Notebooks <notebooks/index.html>`_ > `Portfolio Optimization: Factor Model <notebooks/portfolio-optimization-factor-model.html>`_
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| |github-portfolio-optimization-factor-model| |colab-portfolio-optimization-factor-model| |deepnote-portfolio-optimization-factor-model| |kaggle-portfolio-optimization-factor-model| |gradient-portfolio-optimization-factor-model| |sagemaker-portfolio-optimization-factor-model|
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| Description: Mean-Variance Portfolio Optimization model where the risk estimator is not given explicitly but is instead represented by a factor model, as is common in US equity models [1]. The original notebook is [3].
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| Tags: :ref:`tag-finance`, :ref:`tag-portfolio-optimization`, :ref:`tag-mean-variance`, :ref:`tag-factor-model`, :ref:`tag-ampl-conditonal-instantiation`, :ref:`tag-cardinality-constraint`
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| Tags: :ref:`tag-finance`, :ref:`tag-portfolio-optimization`, :ref:`tag-mean-variance`, :ref:`tag-factor-model`, :ref:`tag-ampl-conditonal-instantiation`, :ref:`tag-mp`, :ref:`tag-cardinality-constraint`
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| Author: :ref:`email-gleb_at_ampl.com` <gleb@ampl.com>
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.. |github-portfolio-optimization-factor-model| image:: https://img.shields.io/badge/github-%23121011.svg?logo=github
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| `Notebooks <notebooks/index.html>`_ > `Solution check: discontinuous objective function <notebooks/solution-check-discontinuous-objective-function.html>`_
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| |github-solution-check-discontinuous-objective-function| |colab-solution-check-discontinuous-objective-function| |deepnote-solution-check-discontinuous-objective-function| |kaggle-solution-check-discontinuous-objective-function| |gradient-solution-check-discontinuous-objective-function| |sagemaker-solution-check-discontinuous-objective-function|
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| Description: Pathological examples to illustrate MP solution checker and settings
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| Tags: :ref:`tag-mp-library`, :ref:`tag-solution-check`, :ref:`tag-non-continuous-objective`, :ref:`tag-strict-comparison`
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| Tags: :ref:`tag-mp`, :ref:`tag-solution-check`, :ref:`tag-non-continuous-objective`, :ref:`tag-strict-comparison`
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| Author: :ref:`email-gleb_at_ampl.com` <gleb@ampl.com>
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.. |github-solution-check-discontinuous-objective-function| image:: https://img.shields.io/badge/github-%23121011.svg?logo=github

‎docs/source/modules/coin.rst‎

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| `Notebooks <../notebooks/index.html>`_ > `CP-style scheduling model with the *numberof* operator, solved by a MIP solver <../notebooks/cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver.html>`_
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| |github-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |colab-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |deepnote-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |kaggle-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |gradient-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| |sagemaker-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver|
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| Description: Scheduling model with the Constraint Programming *numberof* operator, solved with a MIP solver. New MIP solver drivers based on the [MP library](https://amplmp.readthedocs.io/) enable CP-style modeling.
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| Tags: :ref:`tag-ampl-only`, :ref:`tag-constraint-programming`
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| Tags: :ref:`tag-ampl-only`, :ref:`tag-mp`, :ref:`tag-constraint-programming`
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| Author: :ref:`email-gleb_at_ampl.com` <gleb@ampl.com>
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.. |github-cp-style-scheduling-model-with-the-numberof-operator-solved-by-a-mip-solver| image:: https://img.shields.io/badge/github-%23121011.svg?logo=github

‎docs/source/modules/gurobi.rst‎

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| `Notebooks <../notebooks/index.html>`_ > `Portfolio Optimization: Factor Model <../notebooks/portfolio-optimization-factor-model.html>`_
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| |github-portfolio-optimization-factor-model| |colab-portfolio-optimization-factor-model| |deepnote-portfolio-optimization-factor-model| |kaggle-portfolio-optimization-factor-model| |gradient-portfolio-optimization-factor-model| |sagemaker-portfolio-optimization-factor-model|
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| Description: Mean-Variance Portfolio Optimization model where the risk estimator is not given explicitly but is instead represented by a factor model, as is common in US equity models [1]. The original notebook is [3].
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| Tags: :ref:`tag-finance`, :ref:`tag-portfolio-optimization`, :ref:`tag-mean-variance`, :ref:`tag-factor-model`, :ref:`tag-ampl-conditonal-instantiation`, :ref:`tag-cardinality-constraint`
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| Tags: :ref:`tag-finance`, :ref:`tag-portfolio-optimization`, :ref:`tag-mean-variance`, :ref:`tag-factor-model`, :ref:`tag-ampl-conditonal-instantiation`, :ref:`tag-mp`, :ref:`tag-cardinality-constraint`
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| Author: :ref:`email-gleb_at_ampl.com` <gleb@ampl.com>
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.. |github-portfolio-optimization-factor-model| image:: https://img.shields.io/badge/github-%23121011.svg?logo=github

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